Verify if two words are anagram using JavaScript

Anagram Solution in JavaScript

Algorithm challenge: find anagram words. Learn how you can write a function/algorithm to find the check if two words are anagrams of each other.

What is an anagram?

An anagram is a word or phrase formed by rearranging the letters of a different word or phrase. This is typically done by using all the original letters exactly once.

Examples of anagrams

  • Dusty = Study
  • Tar = Rat
  • Arc = Car
  • State = Taste
  • Cider = Cried
  • Bored = Robed
  • Elbow = Below
  • Cat = Act
  • Save = Vase

The challenge

Write a function that takes in two string/words and returns true if the words are anagrams of each other, otherwise, it returns false.


Please note that the solution does not cover the possible edge cases or assumptions.

 * Checks if two strings are anagrams of each other
 * @param {string} str1 a string
 * @param {string} str2 a string
 * @return {boolean}
function areAnagram(str1, str2) {
  // the string lengths must be equal
  if (str1.length !== str2.length) {
    return false;

  // put both strings in uppercase for 
  // case insensitive comparison
  str1 = str1.toUpperCase();
  str2 = str2.toUpperCase();

  // iterate over each of the strings keeping a
  // count of each character in the string in an object
  const obj1 = {};
  const obj2 = {};

  for (let i = 0; i < str1.length; i++) {
    const key = str1.charAt(i);
    obj1[key] = (obj1[key] || 0) + 1;

  for (let i = 0; i < str2.length; i++) {
    const key = str2.charAt(i);
    obj2[key] = (obj2[key] || 0) + 1;

  // iterate over one of the counter objects and check that the count of
  // each character in the object is the same count in the other object
  // return false if not equal
  for (const key in obj1) {
    if (obj1[key] != obj2[key]) {
      return false;

  // else, return true
  return true;

areAnagram('Cat', 'Acting'); // false
areAnagram('Dusty', 'Study'); // true
areAnagram('Arc', 'Car'); // true
areAnagram('Cider', 'Cried'); // true

Time Complexity

The time complexity of the solution above is O(n). Notice that we have 3 loops but no nested loops. Of course you can find even a better solution to this problem. What I have written here is a feasible solution but not necessarily the best.


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